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The increasingly prevalent view that recommendation is a conversation between user and system is driving a renewed interest in approaches to system design that involve the user in meaningful ways. In addition to this the proliferation of mobile devices and the near-ubiquity of sensing technologies means that there are now many opportunities to capture(More)
Recent work has shown the value of treating recommendation as a conversation between user and system, which conversational recommenders have done by allowing feedback like " not as expensive as this " on recommendations. This allows a more natural alternative to content-based information access. Our research focuses on creating a viable conversational(More)
Investigations into combining context and recommendation has resulted in much fruitful research which has improved recommender systems. Such contextual information has come in many forms and been used in different ways, successfully offering better in-situ suggestions. Factors such as location, time of recommendation, etc. have proven themselves as useful(More)
This paper describes work in progress that uses an interactive recommendation process to construct new objects which are tailored to user preferences. The novelty in our work is moving from the recommendation of static objects like consumer goods, movies or books, towards dynamically-constructed recommendations which are built as part of the recommendation(More)
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